Unconditional Generation of SkeGAN:
All of the sketches are generated with a single starting tuple \(S_0\) . Subsequently tuples are generated until the pen-state \(q_3\)  equals 1 or the number of tuples generated becomes \(N_{max}\) . Figure REF  shows some of the sketches generated for the aforesaid categories. Note that the sketches to the left of the separating line in Figure REF  are generated just after the pre-training of the \(G_\theta \) . The sketches to the right of the separating line are generated by the trained model. The visual appeal of the generated images on the right favours the combination of policy gradients and adversarial loss for generating sketches. The images on the left of separating line indicates that pre-training is essential but not sufficient to generate good sketches. It very clear from Figure REF  that the `scribble effect' of [1]} is alleviated by SkeGAN.
<FIGURE>